scrape_clean_markdown

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden; it does add real value by revealing that pages are JS-rendered (so dynamic content is captured) and that the output is normalized Markdown. It is silent on rate limits, API keys/auth for the Firecrawl/Jina backends, failure modes for unreachable URLs, and whether output is truncated or paginated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly packed sentences with zero filler; the capability is front-loaded and the concrete target sites follow immediately as supporting detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity two-parameter read tool with fully covered schema, the description supplies enough: what it fetches, that it handles JS-rendered content, and what it returns. The only omission is what max_chars truncation means for the caller, which is minor at this complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already documented, and the description adds no format, syntax, or semantics beyond that. Baseline 3 applies since the schema, not the prose, carries the parameter burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: a web scraper that turns pages into clean Markdown, naming the underlying backends (Firecrawl / Jina Reader). It implicitly separates itself from the sibling set (outreach/decision-maker/ATS-ops tools) by being the fetch-and-convert tool, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied through the target list — JS-heavy career pages, Ashby/Greenhouse/Workable boards, company sites — which tells an agent roughly when this is the right tool. There is no explicit 'use this instead of X' routing and no statement of when not to use it, so guidance stops at implication.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.